Ben Alamar: Author of Sports Analytics - Sports Business Conversations

Artwork for podcast Sports Business Conversations

Ben Alamar: Author of Sports Analytics

Episode 54 • 27th August 2024 • Sports Business Conversations • ADC Partners

02:18

Dave Almy

. Ben Alamar, the first and foremost, the question I have to ask is, where did the interest in data analytics get started? Have you always been a numbers guy?

02:30

Ben Alamar

Well, I've always, you know, from being a little kid collecting football cards, you know, I always like to look at the stats back and you see all that kind of stuff. And numbers were important. But my real background is in economics. And so when I grad school, I was doing research and, you know, moved into a real data oriented area and was doing policy research eventually as a postdoc, and you start to see the power of data, how you can really learn things that with data, because you can see a large breadth of information and analyze it carefully, which you really couldn't do without good data analysis. And that's exciting, where you learn things that weren't possible without good analysis.

03:09

Dave Almy

So you're doing policy stuff is very qualitative. You're drawing, it's a lot of research, and you're pulling a lot of previous decisions and you're trying to pull that all together. So it has kind of those soft edges to it, I guess, is one way to put it, whereas data is pretty black and white. It's telling you the story, but you still have to have a sort of a qualitative lens that goes against it, don't you?

03:32

Ben Alamar

Yeah, you do. And I mean, the policy work I was doing was really data driven. So were looking at what the impact, economic impact of certain policies were. And so it was always data driven work. But yes, they need to see beyond just what the data is saying and how it fits into the larger scheme is really important.

03:52

Dave Almy

So part of this policy work that you're doing was about tobacco control policy for the University of California, San Francisco, which, for those of you who don't know, is one of the premier medical teaching institutions in the world. That's a long way from sports analytics. So I don't know if it's possible to sum up that transition, but can you give me the dollar tour here? How on earth do you go from smoking cigarettes is probably not the best thing in the world for you to. I want to see if I can help the Oklahoma City Thunder perform better with the debt interpreting.

04:29

Ben Alamar

Yeah. And I like to say that I tell my kids I was a doctor, one of the finest medical institutions in the country, be careful, like they're going.

04:38

Dave Almy

To get people with the ankle surgery calls coming right now.

04:43

Ben Alamar

I was doing things like, were looking at the economic impact of banning, smoking in bars and restaurants. Okay. And there was always, you know, this idea that was going to kill bars and restaurants. Turns out it helps them significantly. And that's power of data that I'm talking about, like some counterintuitive, even for people that are very much for these bands. Like, they were all like, well, at best case scenario, it doesn't have an impact. Well, no, it's actually positive. So we're doing that kind of work. And I, and this was my career in sports is an entire accident. I happened to look at Craigslist at the right time to see posting for a part time consultant for a startup fantasy sports company called Pro Trade Sports.

05:21

Ben Alamar

Pro trade was going to be the first daily fantasy company, basically, and they wanted to do advanced scoring, and they hired me to help work on the market side of it, create, as an economist, help create the market for the different securities of players, set the pricing and all that. And when I got involved, though, I learned about what was happening in sports analytics at the time, which was really, you know, you have Bill James and Moneyball had just come out, and Billy, as a book, the book had just come out. And that was one of the inspirations for the company. So I read the book and I was like, oh, I wasn't a baseball fan, so I didn't know any.

05:57

Dave Almy

Not at all. Were you a sports fan at all?

05:59

Ben Alamar

Huge sports fan. I grew up in Washington, DC with the Joe Gibbs run there, which was unbelievable and, you know, were nothing unbelievable at all. But, you know, those basketball and football were my sports. I, we didn't have baseball in DC, and I played lacrosse, so we really didn't like baseball.

06:18

Dave Almy

Oh, you and I have something in common.

06:20

Ben Alamar

Oh, there we go.

06:21

Dave Almy

We'll have to have a follow up on that. Volume two.

06:24

Ben Alamar

Yes. There you go. But there was this starting of work in basketball. Dean Oliver had just written basketball on paper. Aaron Schatz with football outsiders had just come been started. Aaron Schatz was part of this group. Roland beach, who would go on to work in the NBA for a long time, had just started a site called 82 games.com. And so I got to meet all these people that were doing this really interesting work that I thought was really excited about but just didn't know was possible. And so as soon as I saw that, I was positive, like, you know what? It's really the kind of work I want to do. Like if my training as an economist can lead me into a sports career, like, that's exactly the kind of thing I want to be able to do. And so that's where it started.

07:07

Ben Alamar

I knew the work with pro trade sort of snowballed, and I ended up getting the opportunity with the Thunder. And I started, you know, at the time, I was imagining an academic career for myself, so I started the first journal of sports analytics called the Journal of Quantitative Analysis and Sports. So I would have someplace to publish work and I gotta have someplace I.

07:26

Dave Almy

Can put my stuff in. So I better read the magazine.

07:29

Ben Alamar

Yeah, at the time, and this is radically different at the time, though, because.

07:33

Dave Almy

It does so speak to how new this all was.

07:34

Ben Alamar

e, and this is, I want to say: 2005

08:02

Dave Almy

Really?

08:03

Ben Alamar

Yeah. Oh, yeah.

08:05

Dave Almy

Sports was seen as a hobby.

08:08

Ben Alamar

Yeah, it's a hobby. It's not serious. And part of the reason for that is there's no place to publish it reliable. And so we had to do that. But there were no courses on sports analytics. There was nothing like that. There was no real. At the time. Nobody was doing it. And so fast forward today, 20 years later. Rice university has a major in sports analytics. Now, several other. I mean, they're not the only one. Several other universities do. School has classes on sports analytics. Most schools have clubs for sports analytics. I have high schoolers now doing sports analytics hackathons and asking me about how to do a career in sports analytics. It's an entirely different world.

08:52

Dave Almy

Was there an inflection point that you can recall where it kind of tipped from being. Don't do that unless you have tenure. It'll be a dead end. People won't take it seriously. To high schoolers now calling and say, how to do a career in this.

09:04

Ben Alamar

I think it's like, it's hard to say it's gradual because it's happened so fast, but it has sort of constant increase. As we started the journal, as people, more professors did start to publish, more classes, started to get, be taught, there was a, and there were more, and there was just a constant growing opportunity in the, in different leagues, in different areas for the work. Like, that's. The other part is at this time, you have, you know, when I started, I was the entire analytics group for the Thunder, and I was.

09:35

Dave Almy

It's called. That's using the word group lightly when you're the only person in it. Right.

09:41

Ben Alamar

At halftime, like, that was all. Now most NBA teams have seven, eight people at least, and baseball teams are in the twenties. NFL teams are rapidly catching up. These are like, because there are now places for people to go work and do this kind of stuff. That's growing. There are more classes and more people interested. It's just been this really amazing growth of the industry over time.

10:04

Dave Almy

And was that the impetus for writing the first edition of Sport analytics? Right. The journal had to be published, a place to do the academic work to bring it more to legitimacy than you. You start to see the growth of the programs, then it lacks sort of a foundational text.

10:19

Ben Alamar

Well, so it's interesting because the text itself is not for most of the people that take the classes, because it was born out of a class. I was teaching at University of San Francisco.

10:30

Dave Almy

Go dons.

10:31

Ben Alamar

Yeah, exactly. In the sport management program. And it was for people who were not data scientists. Some of them hadn't even taken statistics before they got to my class.

10:41

Dave Almy

Right.

10:42

Ben Alamar

What they needed were the tools to that. This massive new thing was coming into the industry, both on the business and the sports side of the world, and they needed to be able to understand it, they needed to know how to manage it. They're going to be the people that are making the decision about how much to invest in analytics. So they need some kind of basis to do that. The text is written for them, for the managers, for the leaders, on how to best utilize and how to get the most out of your analytics investment.

11:11

Dave Almy

So really to pull back the curtain on the potential of this tool that can reshape their industry. So can you talk about that for a minute? Because I think the concept of moneyball, given the book and the movie and everything like that, I think that concept is more or less well understood from the performance side, like really breaking down athletes and what they can do in certain situations. Can you speak to what the impact has been for the business or front office side of sports? Where does that really start to be? Like an oh, wow moment for some of the people who have read sports analytics?

11:51

Ben Alamar

Yeah. On the business side, it's, you know, so much is about knowing your fan. If you go back, you know, again, 20 years ago, what did we know about the fans?

12:00

Dave Almy

Ate a lot of hot dogs, put the butts in the seats. That was pretty much what you did.

12:04

Ben Alamar

That's about it. Now we know who the fan is that buys the season ticket. We know who they've sent that ticket to that's going to join them at the game. We know we can try and join that with all kinds of other data about them in terms of their activities, whether it's social media activities or other transactions and other platforms on the team's website, whatever it is, you can start to track all that stuff and really get a good idea of who the fan is and how frequently they come to games, how they get engaged, how what they spend in different areas. All of that is now possible. You get. And now. And we can target fans and targets, sometimes a loaded word.

12:44

Ben Alamar

It feels like you're trying to get some out of, but really you're creating value for the fans and like they're opening opportunities and things for them that they maybe didn't weren't aware of, weren't aware in this particular area. And so it's a great. The data has helped us really understand fans and segment them into the groups so that we can help them best engage with the teams that they love.

13:05

Dave Almy

I think it's one of those conceits when you're working for sports business, you're day in and day out trying to figure out how you monetize different things and how you become more efficient and things like that. But from the outside looking in, it's sometimes easy to forget that these are money making machines. It's not just the entertainment part of it. And that so much time and energy is spent carving out the different pockets of opportunity to generate more revenue out of this. And this is where data really starts to hone in on this. You take the big pool and just make these broad based decisions now you really start to concentrate on personalization, unique products that really cater to what you're learning with what all the data is telling you, aren't you?

13:49

Ben Alamar

Yeah, you can. For example, the women's sports is exploding right now. Like, you know, we've seen these massive growth over the last few months, but it's going to be a really different market and different kinds of messaging is going to be effective. And so you have to test those things. You have to have email experiments running to try and figure out which are the most effective ways to engage different groups that are becoming these new fans of this game. And so it's exciting and going back to my original sort of reason for days, like, you get to learn stuff about these fans that you wouldn't have known otherwise, and that's fun for me. And then it's really valuable to the organization.

14:30

Dave Almy

It's funny, I did an interview not too long ago with Christopher Zuck, who is the founder of CAS Investments, and he does a lot of private equity work with sports teams. And he's had this whole opportunity, given the professional leagues now making it possible for private equity to come in and own parts of teams. He says that one of the best values that they have is they can now data share across what they're learning from all these different teams. And you've just made a blanket statement like, look, if you're not using data analytics, machine learning, and AI in sports, you are done. There's just no way you can compete anymore.

15:08

Ben Alamar

No, you absolutely can't, because there's too much value in it. You can see and learn and specialize in an automated way. It creates efficiencies, it creates new information that is just not possible to get in any other way.

15:24

Dave Almy

What teams do you see right now who are really doing an effective job using data analytics? Are there standouts in the industry that you even like? Someone who's as deep in it as you are kind of go, wow, that is advanced stuff.

15:38

Ben Alamar

Yeah. Sometimes it's hard to know what's going on within a team because unless actually they're not going around saying, hey, did you see this? Cool.

15:45

Dave Almy

You just don't open the door and say, hey, what's going on in here? With all the teams?

15:48

Ben Alamar

They're interested in sharing that kind of stuff because particularly on the performance side of the world, that's the competitive advantage. That's why they do it. On the business side, it's a little less so. They are more partners than any, but.

16:02

Dave Almy

It'S a weird business that way.

16:03

Ben Alamar

Yeah, but you see a team like the Boston Celtics, that's easy to pick, a team that just won the championship. You can see that the team was constructed differently than other teams, and now everybody's rushing to copy what the Celtics did. But I mean, they were ahead of the game and they saw some things that and what exactly they say, how they brought things together. All I know is that you have some really good people working there. Same is true for, you know, the sixers. Obviously, Daryl Morey is there and he is one of the leaders of the industry for sure. And so they're doing a lot of good work. I mean, it's really been amazing to watch, as I said, everything grow, and it was ten years ago. It would be easy to tell you, well, this team is great.

16:53

Ben Alamar

That team is not. There's differences and quality matters still, but there's. Most teams are much closer to each other. The spread is less than it used to be.

17:04

Dave Almy

And I think most teams understand now, like, there may have been some resistance to data analytics amongst, quote unquote, old school people and go with my gut type people from the past, but I think that's largely done and a lot of teams are out there putting these kinds of programs in place, putting together teams to evaluate data more effectively. But it's not easy. Right. These are challenging. You're sort of learning this new skill as you're building the car as it's racing down the freeway. So where are the challenges about making better use of data like, and what are the missteps that can be avoided from your perspective, having seen some teams do this and sort of done some.

17:46

Ben Alamar

Research along the lines of it's interesting there are both for the book, for both editions of the book, I did a survey of professionals in sports analytics. And in both cases, both times I was, I pulled the results from a particular team that had multiple people answering it. And you could significant misalignment people on the team about what their goals were, how they did things, what was actually happening, how effective things were, what the priorities were. Yeah. Or even like this kind of data is widely available. Like some people would in the same team would say, yes, widely available. No, not widely. Like really divergent opinions. And so it's really.

18:27

Ben Alamar

So first, you know, as you're managing a team, making sure everybody's aligned on sort of what you're trying to do and realistically where you sit, how far you have to go to be really good at what you do. But that's sort of a management thing. On the sort of technical side, getting the data right is the key. Like without that, everything else gets harder. Everything else is still possible. It's just harder.

18:51

Dave Almy

When you say, I want to just interject for a second because it's a really interesting point to me, it's getting the data right seems like such a simple statement, but that's actually enormous. Right. So can you tease that out just a little bit? Like when you say get the data right, what does that mean to you?

19:13

Ben Alamar

So if you think about all the different sources of data that a team has to deal with, right. There is data coming directly from the lead. There's data coming from a variety of data vendors that they utilize. There's data being created within the team, so people recording, tracking things and things, putting a system together that centralizes all of that information so it can be efficiently accessed and combined is the key.

19:44

Dave Almy

Yeah, boy.

19:46

Ben Alamar

Otherwise it's really easy to end up with these big data silos where you have particularly your strength and conditioning. Coaches are entering all their data into this one system that doesn't talk to anything else. And if that's the case, you cannot use that information to help with the analysis of any other thing. And so unless you will think that information is not important for the long term performance of your players, which most people don't, that hurts you. And so designing the system at the beginning and having the organization understand all the data has to flow in this way and it gets combined and integrated in this manner, that gives you the foundation to do a whole lot of stuff really well.

20:28

Dave Almy

Its been interesting to watch sports focused companies and im thinking particularly on the ticketing side right now because its one of the more forward facing ones that people interact with on a regular basis. Right. People go to the stadium, they buy a concession. Thats sort of in the background of their mind. They dont really realize that data is being collected. But on the ticketing side, the Pachyolans, the Ticketmasters, they're as much data platforms right now as they are facilitating that ticket purchase because there's so much value in that data. And to your point, collecting it in a right way, in a usable way.

21:05

Ben Alamar

ith this. I was at Stubhub in: 2019

21:51

Dave Almy

Well, I had the opportunity to work with Learfield for years at the point where their current CEO, Cole Gahagan came in. And that was the inflection point. Like, before he got there, they were selling signs and radio, and they were sort of just this marketing company. When he came in, he's like, you know, we're gathering data from fans, from Pachy Olin, from our sidearm piece, they had all this concentrated data. So his sort of light bulb moment, was that what you just discussed? Yeah.

22:20

Ben Alamar

Okay.

22:20

Dave Almy

We're a sports company, but we're really a media and technology company. When you get right down to it, which offers so much to advertisers, the potential of showcasing what this audience is and how they can reach it.

22:31

Ben Alamar

And then once you can think of yourself that way, you can make this serious investment in both the technology and the people. You need to be a technology company.

22:39

Dave Almy

And the people is really where the rubber hits the road as far as both where they're getting skilled. But also, like, to your point in the book, being conversant enough in this category of business to be able to make effective decisions, to be able to give to your .1 of the challenges is how do you give that team direction? And so, Helm, what was the delta between when you wrote first edition and second edition? How many years had passed?

23:11

Ben Alamar

Ten years.

23:12

Dave Almy

Okay, so ten years. So, in technology terms, it's a lot. I mean, multiple geological ages, as far as. I'm assuming that was one of the big catalysts for doing it.

23:22

Ben Alamar

Yeah, I mean, it's interesting. The technology has certainly skyrocketed, is way different, and the things we can do now are significantly more advanced when I first wrote the book. So the fundamental things that you need to understand and the challenges that we face are all very much the same. That part doesn't change very much. What changes is the things that you can actually do, the kinds of questions you can actually try and answer. But the fundamentals of, we need to centralize this data so we can do anything with it that's still the same. The tools you use to do that, they're much better now. It's much easier to do that. It's still not easy, but it's much easier to do it now than it used to be.

24:03

Ben Alamar

But the needs, the things that you have to do to get right to be the most effective data science group you can be, are still the same. It's just we can do a whole lot more in it.

24:15

Dave Almy

Was there anything, I mean, other than the facility of using the data and the number of tools available? I'm wondering, as you started adding on to or modifying additional, so it became the book of sports analytics, and it's now in volume two. Where were some of the moments where you kind of went, my God, this is so different from how it was when I first did the book. I mean, this is. I can't even. I got to start basically from scratch. Yeah.

24:41

Ben Alamar

I think one of the biggest difference, and really what fueled a lot of the growth of the industry itself on the performance side was the availability of tracking data. And this, in the NBA, you have cameras that record the location of everything that moves across the court times a second. Now they're doing it in three dimensions.

25:01

Dave Almy

We don't want the streakers caught in three dimensions on an NBA court. We don't want everything. We got to screen that out.

25:07

Ben Alamar

Yeah, so, I mean, that. That data in the. And it's true in every single sport is the. The catalyst for rapid expansion of the analytics groups and understanding, because it's the data that allows you to ask questions that you could never even imagine to ask of data before you can ask. Well, when Steph Curry has the ball and they're running a pick and roll with Draymond Green, should we go over under the pick? Data had nothing to do, say, play by play. Data cannot like, what's that, I don't know what that means. Now with the tracking data, you can actually ask that question and immediately look at all the clips where that happened, see how teams did it and see the results and understand them from the day, how effective different defensive strategies were at different points in time.

25:52

Ben Alamar

So that's a massive game changer that required teams to invest more, grow their groups. And now as you grow groups, what you're doing is you're changing the whole nature of it. Because instead of like, I'm going to hire two or three of the best data scientists I can find, now I've got to have a team, and running a team is really different than being two or three great data scientists. Now, maybe I need, I'm talking about specializing. I've got data engineers and data scientists, and maybe I've got somebody who specialized in being the bridge between the analytics team and the coaching staff. I've got maybe somebody who's embedded with the front office, or maybe I need a product manager to help everybody make sure that we're keeping on task and building things as effectively as we can be all the time.

26:41

Ben Alamar

All these kinds of. As the teams grow, the complexity of running that team grows.

26:46

Dave Almy

It's interesting that we're talking about something as black and white as data and the power that it can have. But ultimately, it sounds like one of the biggest challenges. It's still just a managerial problem, it's.

26:56

Ben Alamar

A people problem, 100% getting the most out of now. And it's a bigger problem now because again, two or three data scientists, that's that. Particularly in the early days, that was like pocket change because people were doing it for almost nothing. Now you talking about a group of 15 people that and the tools they need, the investment you need, it's a large investment. The teams are making. You need to make sure you're getting the most out of that investment.

27:23

Dave Almy

But it also speaks to no sports team in the world is going to invest money in something that's unproven, right? They're going to pilot it, they're going to test it, they're going to ask for it for free in exchange for sponsorship and stuff like that. Sports teams are famously a little, I won't say tight fisted, but they're famously reluctant to part with dollars without like, okay, if I spend this money, I want like ten x return on it. So I guess it speaks to how much the return has been on data analytics that these, not only these teams have grown so quickly, but there's so much investment in tools and capability.

27:59

Ben Alamar

Absolutely and you can see it in the salaries for the teams. Like, you know, now there's always going to be a sports discount. Like, that's all. Like, every data scientist thinks about sports knows that. But the sports discount has gotten much less over time. Part of that is because teams, as you say, realize that there is something valuable here. Part of it is teams realize we do have to, like, if we want the best, if we want, we say we want to have the best people on our teams, we need to pay the best people, because not all the best people are willing to take a massive discount to work in sports. So you have to, you know, so there's been an upward pressure on salaries.

28:37

Ben Alamar

You know, back in when I started, like, it was, you know, they were hoping to pay people straight out of, you know, school, you know, $35,000 a year to be there, you know, a data scientist for them. You know, that's, again, we're not, there's.

28:53

Dave Almy

Some data scientists listening to this right now going, what I had.

28:58

Ben Alamar

One intern with one team who was, he had played basketball at BYU. He was the greatest kid in the world, just gotten his masters in statistics, really wanted to come work on the team. The team wanted him to be on the coaching staff and they offered him $50,000. What are you talking about? And the GM was like, well, that's my first job in the NBA. Was a lot less than that. Doesn't matter. He took a six figure job and is doing just fine. Thank you.

29:26

Dave Almy

Yeah, I think he probably made a decision that was going to be good for him in that particular regard. Right, but that's also the change here, right? I mean, this is the history of people in managing sports as well, because people want to work here. I've heard it a hundred times. You know, you'd like your salary like what you're doing because there's 35 people waiting in the wings to take your job.

29:46

Ben Alamar

Absolutely.

29:47

Dave Almy

But the strength of data analytics and what that could come in on the open market changes that game a little bit. Not to. I'm sorry, that's a terrible punitive. This is a discussion about data and analytics and machine learning and using that data. So it has to have a quality of artificial intelligence tied to it only because it seems like I think I have an AI toothbrush in my path. So as you look at AI and how quickly that's been adopted across all industries, how does that start to shape how teams and sports organizations, in your mind, how is that going to start shaping how they interact with data.

30:32

Ben Alamar

I think it depends a little bit how we define AI. There are lots of different mechanisms. When we talk about the tracking data, is that AI to be able to record the angle which a shooter is taken, they're shot from?

30:50

Dave Almy

Yeah.

30:50

Ben Alamar

I mean, who knows? But what we can say is that these models that analyze data have gotten much better, more efficient, more complex, and much more flexible. They can take in more inputs and more types of inputs than they could ten years ago. So now, it used to be, if I wanted to analyze video, I would have to track it down. We would mark it down and code it in some way, and then feed that into an algorithm and see what comes out. Now you can feed data into the algorithm, just the data, just the video itself, and it can take that and turn itself into data and utilize that. And that's some part of the thing that's really powerful, because organizations don't rely on just quantitative data at all. They have scouting reports.

31:40

Ben Alamar

They have, or if you on the business side, memos, like we have PowerPoint presentations. We have all this wealth of information that back up different kinds of outcomes and decisions that we made. We can now. You can now start to feed all of that kind of unstructured data into these algorithms and start to understand things and see opportunities, whether it's in business or on the field of play that you couldn't have seen before. So it massively increases the amount of data you have, which is expanding, making your asset itself much bigger, and then helps you point it in new and creative ways that you may not have been able to see otherwise.

32:25

Dave Almy

The book is sports analytics. It's in its second printing. It's just been updated after a ten year version difference between volume one and volume two. So I'm going to ask you the easiest question in the world. I expect you just kick up your feet, and this will be super easy for you, right? So as you look ten years down the road to volume three, what are you already looking at and going, God, this is on the horizon? Organizations need to be paying attention to this. What are the keys that you see as you start to think about? Okay, here's what goes into volume three. What's that gonna look like? Is it even gonna be in book form? Is it just gonna play? Like, is there gonna be a USB port in the side of my head?

33:02

Dave Almy

You're just gonna plug it into, goddess, please let it be so.

33:04

Ben Alamar

Yeah, yeah, something like that. I think that one of the things that we touched on a little bit is this idea that if we have any of the growth that the people in the industry are telling me we're going to have in the survey, 80% of the people that I surveyed said their teams are growing. So you can start to imagine where we're going to be in terms of size of analytics teams and complexity of those teams in ten years. That again, is going to require a much even more thoughtful, careful planning and strategic use of those resources and how you're investing those things. So you are getting the most you can out of them on either the business or the performance side. I think we're going to see teams trying one of the most powerful tools in data science, generally speaking, is experimentation.

33:54

Ben Alamar

And you can do that on the business side all day long. We talked about sort of email campaigns and stuff like that. You can do that. Teams haven't really gotten figured out a good way to do any kind of experimentation actually on the performance side, because no coach is experimenting. Coaches were trying to win. They're doing whatever they can to win. AI, when it's really good, is going to potentially create areas where we can set up experiments within the AI and let the AI run the experiments in virtual worlds that are really realistic. I mean, we can already run simulations and see the little differences, but we need to be able to have really strong simulation tools and be able to take in lots and lots of dimensions of data to do good experimentation.

34:42

Ben Alamar

So if I change my defensive coverage in one way, very subtly, does that have a positive or negative impact? I don't know until I can really run it and then have different players in that, different positions like or then one of the things we worked on at ESPN when the NFL next gen data was first coming out is quarterback decision model. So using that data, Brian Burke, who's brilliant data scientist at ESPN, invented basically football analytics, was creating this model that looked at how well quarterbacks were making decisions and what we can do eventually as the model improves and everything, we can now swap out quarterbacks between teams and make better free agent decisions. Like if I put this quarterback on this team and I run the same offense, what's good?

35:34

Ben Alamar

Or how do I need to change my offense now that I'm stuck with this quarterback to make it better? Like all these kinds of things, we can start to ask these questions of the data and that's really exciting. That's we're not there yet. We have a few years to go, but it's certainly going to get there.

35:49

Dave Almy

And going back to the other point about people, right? You have coaches who are so focused on winning. This is the way we got here. This is the way we do things. To your point, you can experiment in the sandbox and virtual worlds. You still have to have people buy into what that capability is and what it's showing you.

36:07

Ben Alamar

Right? And that's one of the interesting things. Like, at some point there, you know, somebody's going to have a really good analysis of, and it's going to sell, tell us to do something really weird and, like, something that people aren't going to want to do. And the first team, and maybe it'll be right, maybe it will be wrong, but, like, somebody's got to try it and then, boom. Like, it's, you know, right now, if you look at the NBA, I mean, this is a very basic example, but if you look at the number of threes teams take now, and the number of threes they took 20 years ago, if you told a team 20 years ago, oh, you should, 50% of your shots should be threes now, they would have said, that's insane.

36:46

Dave Almy

Insane. What are you talking about now?

36:49

Ben Alamar

That's. Now? That's winning championship right now.

36:52

Dave Almy

That's scripture now in the NBA.

36:54

Ben Alamar

And so, like, that's a massive change brought about by data. Brought about by data. Well, to a certain extent, it's brought about by simple math. You know, three apps. That is more than, hey.

37:06

Dave Almy

For a simple math people. That's what we're talking about here, Alomara. Well, you know, come on now. We gotta have the liberal arts majors gotta chime in at some point here. I'm with Ben Alomar. He is the author of sports analytics. It just released its second edition. It's now available. You can buy it on Amazon. Ben, thanks very much for spending the time, but before I let you go, I got a bunch done the lightning round. Do a series of questions. You gotta brace yourself a little bit. Let me know when you're ready. You wanna stretch first?

37:32

Ben Alamar

Let's do it.

37:33

Dave Almy

Let's just get right into it. Okay. Ben Alamar, in the lightning round, you got your bachelor's at the University of Minnesota. You got your PhD in at the University of California, Santa Barbara. How much was weather a factor in the decision to go there?

37:48

Ben Alamar

I applied to ten graduate schools. Eight of them were in California, so.

37:57

Dave Almy

I'm going to go with pretty significant. All right, you're currently working at a consumer facing technology company. Does appearing on a podcast qualify for a family and friends discountenhein?

38:09

Ben Alamar

Unfortunately, no.

38:10

Dave Almy

That laugh did not say absolutely, Dave. Okay, you've barely got me beat in alphabetical order. You're Al. I'm a l M. You're a l A. So I'll give you 5 seconds to gloat.

38:22

Ben Alamar

Well, it's always good to be first.

38:26

Dave Almy

You've lectured at schools including University of San Francisco, MIT, Columbia. Which campus has the best dining food?

38:33

Ben Alamar

Oh, that's a good question. I mean, Columbia, I mean, you're right. In New York, it's really easy to get great food around there. So I'll probably go with Columbia.

38:41

Dave Almy

Probably go with Columbia. That's probably a good thing. All right. And as we've talked about, the speed of change in data is coming really fast. How long before version three is in the market?

38:49

Ben Alamar

Well, I mean, we're on a ten year pace, so, you know, check in.

38:53

Dave Almy

Come on, man. We're talking about geometric change. We're going to get to be five years. Now get writing.

38:59

Ben Alamar

I can't do it in five years. That's too much work.

39:02

Dave Almy

Ben Alomar. Appreciate the time, man.

39:04

Ben Alamar

Thanks for having me.

39:06

Dave Almy

Thanks for listening to this episode of the one one sports Business Conversations podcast. If you enjoyed it, we always appreciate a subscribe, share, comment, or like. And don't forget, you can always find past episodes@abcpartners.com. Podcast this podcast is written, produced, edited and hosted by Dave Almey, and theme music was composed by Scott Holmes.